Essays on applied spatial econometrics and housing economics

by 1977- Kiefer, Hua

Abstract (Summary)

Housing purchase represents one of a household’s most signi…cant economic decisions.
The ancient joke in real estate is that the three most important criteria for
selecting a house are location, location, and location. This explains the great emphasis
of a household on residential location choice when he/she is buying a home.
Driven by households’demand on location, it should also play an important role in
determining house prices. As a key determinant in household consumption behavior,
locational context or neighborhood e¤ects is worth investigation. This dissertation
examines locational/neighborhood e¤ects in the housing market using spatial econometric
methods.
The …rst essay studies the importance of social interactions in a household’s location
decision. I argue that individuals prefer interacting with others who have
similar socioeconomic backgrounds. The hypothesis that a household desires to …nd
a good community match is tested through the application of a discrete residential
location choice model. An unwritten rule in real estate is that one should buy the
cheapest house in an expensive neighborhood, which is formally the Tiebout hypothesis
that households search for a community where their bene…ts from local public
goods will exceed their local tax costs. The community matching hypothesis and
the Tiebout hypothesis have di¤erent implications regarding a household’s residential
location choice. Community matching implies households will prefer similarity,
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while the Tiebout hypothesis implies households will prefer neighborhoods with richer
neighbors. I use a nested logit (NL) regression to analyze a household’s residential
community decision within Franklin County, OH. As an important input of the NL
regression, a set of housing price indices are created through a spatial error model.
The regression results support the hypothesis that a household prefers neighbors with
like socioeconomic characteristics in almost all of the similarity dimensions and only
prefers an a­ uent neighborhood to a moderate degree.
The second essay employs a spatial autoregressive model (SAR) to estimate housing
asset prices. Applying the rational expectations hypothesis, this essay models the
current value of a housing unit as the conditional expectation of the discounted stream
of housing services accruing to the owner of the house. Based on the importance of
location, the value of housing services is determined by neighborhood e¤ects as well
as the physical attributes of the property itself. In the existing hedonic literature,
the neighborhood e¤ects are only ascribed to prior transactions in the neighborhood.
After employing the generalized method of moments (GMM) in estimating the spatial
asset pricing model, I …nd that both expected future transactions and prior transactions
in the neighborhood are signi…cant in explaining a house’s price, and the
explanation power of future neighborhood transactions is statistically equivalent to
that of past neighborhood transactions. The inclusion of expected future transaction
prices in the neighborhood takes into account the in‡uence of expected changes in
the community and factors these potential changes into the house prices. This is consistent
with the forward-looking behavior of households. The forward-looking model
generates superior out-of-sample prediction performance relative to the conventional
hedonic model.
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